Artificial neural networks and neuro-fuzzy systems for modelling and controlling real systems: a comparative study

Vieira, José Barros; Dias, Fernando; Mota, Alexandre

http://hdl.handle.net/10400.11/2135

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Authors

Vieira, José Barros

Dias, Fernando

Mota, Alexandre

Abstract(s)

This article presents a comparison of artificial neural networks andneuro-fuzzy systems appliedfor modelling andcontrolling a real system. The main objective is to model and control the temperature inside of a kiln for the ceramic industry. The details of all system components are described. The steps taken to arrive at the direct and inverse models using the two architectures: adaptive neuro fuzzy inference system and feedforward neural networks are described and compared. Finally, real-time control results using internal model control strategy are resented. Using available Matlab software for both algorithms, the objective is to show the implementation steps for modelling and controlling a real system. Finally, the performances of the two solutions were comparedthrough different parameters for a specific real didactic case

Keywords

Temperature control Fuzzy hybridsystems Artificial neural networks Applied neuro-fuzzy control Model-based control Real-time control

URI

http://hdl.handle.net/10400.11/2135

Citation

VIEIRA, José; DIAS, Fernando; MOTA, Alexandre (2004) - Artificial neural networks and neuro-fuzzy systems for modelling and controlling real systems: a comparative study. Engineering Applications of Artificial Intelligence. ISSN 0952-1976. Vol. 17, nº 3, p. 265–273